Private AI

Useful AI without a public model data path.

Private AI in BlackBox Node means local retrieval, local model execution, controlled source access, and permission-filtered context for organisations that cannot responsibly send sensitive data to public cloud AI services.

No public prompt path Local model runtime Permission-filtered context Client-controlled deployment Reviewable outputs

Data path

The sensitive path stays local

The product direction avoids sending confidential documents, prompts, retrieved context, or generated sensitive answers to external cloud model providers.

Runtime abstraction

Local model runtime first

Ollama is the first runtime abstraction direction, with llama.cpp planned later for tighter packaging and control where needed.

Governed assistance

Assistive, not autonomous

The product should help professionals search, draft, compare, and review information while preserving professional judgement and local governance.

Private AI path

Local context stays under local control.

The private AI story joins local storage, local retrieval, local generation, and professional review in one controlled appliance pattern.

  1. 01

    Keep data local

    Sensitive content remains in the client-controlled appliance environment.

  2. 02

    Select permitted context

    Retrieval is filtered by role, user, matter, client, and case permissions.

  3. 03

    Run local model

    A local model runtime receives only permitted context for answer support.

  4. 04

    Review with citations

    Professionals review generated drafts against source references.

  5. 05

    Audit usage

    The appliance records non-sensitive operational activity locally.

Public website boundary

This site explains the product. It is not the appliance.

This public website is product information only. Do not submit confidential client, patient, case, investigation, regulated, or commercially sensitive data through the public website.

Next step

Discuss a private intelligence deployment.

Use the contact path to talk through data sensitivity, sector obligations, appliance shape, and rollout readiness before implementation decisions.